The team, affiliated with the Laboratory of Tribology and Dynamics of Systems at École Centrale de Lyon and CNRS, Tohoku University’s Advanced Institute for Materials Research, and RIKEN iTHEMS, addressed a design problem that becomes increasingly difficult as the size of a textile pattern grows. Even a 10-by-10 weave has more possible yarn arrangements than could realistically be tested individually, and a detailed acoustic simulation can take more than an hour. The researchers sought a way to reduce the number of candidates that required expensive simulation while retaining patterns compatible with basic manufacturing and connectivity requirements.

They began by generating woven patterns that met those structural constraints, then grouped the patterns according to four types of repeating symmetry, including rotational and mirror symmetry. An AI system organized the patterns on a design map, placing structurally similar designs closer together. The researchers simulated a selected set of designs and used those results to train a prediction model.

Once trained, the model could evaluate candidate designs and direct a computer search in less than a minute. Independent, detailed simulations of selected designs were then used to check the predictions, which agreed with the simulation results within 5%. This agreement concerns modeled sound absorption, not measurements from physical acoustic tests.

The study also showed how symmetry can act as a physical design parameter rather than only a visual property. Woven patterns differ in how they distribute yarn crossings, and those crossings shape the microscopic gaps through which air moves. Some arrangements create more winding airflow paths, increasing opportunities for sound energy to be dissipated through friction and heat; others leave straighter and more open paths.

The size of the smallest repeating unit also affects the range of airflow and acoustic behaviors available. Lead author Thanasak Wanglomklang said the approach allows researchers to explore woven structures that would be impractical to examine through trial and error. He emphasized that the method “does not replace physics; it uses physics more strategically to identify promising, manufacturable designs.” Machine learning did not independently determine how sound would interact with a material.

Instead, physics-based simulation supplied training data, symmetry provided an organizing framework, and AI accelerated the identification of designs for closer physical evaluation. The study was published in Communications Materials on 27 August 2026 under the title “AI-assisted symmetry-informed topology optimization of woven materials for broadband sound absorption.” Experimental validation is the next stage.

The team plans to manufacture selected three-dimensional woven prototypes and test their sound absorption experimentally. It also plans to extend the method to multilayer woven materials, larger repeating structures and variations arising from manufacturing processes. Until those tests are completed, the supported result is a faster symmetry-informed route for prioritizing manufacturable candidates in a vast design space, together with close agreement between model predictions and detailed simulation.

The study does not yet demonstrate an improvement in experimentally measured sound absorption.

Subject of Research: Computational optimization of woven textile patterns for broadband sound absorption

Article Title: AI and symmetry accelerate the design of sound-absorbing woven materials

Article References: AI and symmetry accelerate the design of sound-absorbing woven materials. Original publication (Bibliographic details unavailable.)

Image Credits: AI Generated

DOI: Not provided

Keywords: AI-assisted design, sound absorption, woven textiles, symmetry analysis, machine learning, acoustic simulation, materials optimization, topology optimization, multilayer materials, symmetry, accelerate, design

A team led by Qihang Liu and Xiaobing Chen of the State Key Laboratory of Quantum Functional Materials and the Department of Physics at Southern University of Science and Technology, together with the Quantum Science Center of the Guangdong–Hong Kong–Macao Greater Bay Area, has now turned that exercise into an automated workflow. Their open-source online platform, called FINDSPINGROUP, is reported in National Science Review. The tool places magnetic-moment arrangements and spin-orbit effects within a single, material-specific symmetry framework, allowing researchers to ask, in a consistent way, which responses a material’s magnetic geometry permits, and which additional responses emerge once spin-orbit coupling is switched on. The distinction is not academic. Knowing which mechanism drives a given response determines how that response will behave when the magnetic order is rotated, switched, or embedded in a different crystal environment, and it guides which materials deserve the expense of demanding calculations and experiments.

The conceptual heart of the platform is a reconciliation of two symmetry descriptions that have historically lived in separate regimes. In the absence of spin-orbit coupling, a magnetic material is described by a spin space group, in which operations acting on spins are not required to follow the corresponding rotations of the crystal lattice. Once spin-orbit coupling locks spin to lattice, the appropriate description becomes the magnetic space group, in which spin and lattice operations move together. Each map works well within its own regime, but the two are not automatically aligned. A spin space group is unchanged when the entire spin frame is rotated, so on its own it does not specify the physical orientation of spin operations relative to the crystal. A magnetic space group, by contrast, already assumes that this relationship is fixed. Different choices of unit cell, basis vectors, and origin add further complications, so comparing the two descriptions for a real material has meant identifying and realigning them by hand.

Liu and colleagues resolved this with the oriented spin space group, or OSSG. The OSSG selects the material-specific orientation of the spin operations relative to crystallographic directions, without itself introducing spin-orbit coupling. From this common starting point, two analyses branch out. The full OSSG provides symmetry constraints for the material without spin-orbit coupling, while the subset of operations that remain compatible with spin-lattice locking forms the corresponding magnetic space group and supplies the constraints that apply when spin-orbit coupling is included. Both branches generate crystallographic information and restrictions on magnetic and transport properties, and because both are expressed in the same coordinate frame, their predictions can be compared directly. “The important question is not only what symmetry a magnetic material has, but where each of its allowed responses comes from,” said Liu. “By placing magnetic geometry and spin-orbit effects in the same material-specific frame, the OSSG allows the two contributions to be compared directly.”

FINDSPINGROUP turns this framework into a practical pipeline. A user supplies a magnetic structure in CIF, MCIF, or the newly introduced SCIF format. The platform identifies the material-specific OSSG, converts the result to a standard crystallographic setting, matches it to a canonical database representative, and derives the corresponding magnetic space group in the same coordinate frame. It then interrogates the material with what amounts to two parallel questions: what does the magnetic geometry permit without spin-orbit coupling, and what additional responses become possible, or disappear, once spin-orbit coupling is included. To answer them, the software produces standard magnetic cells, spin Wyckoff positions, spin site-symmetry groups, spin Brillouin zones, and symmetry information at high-symmetry wave vectors. It evaluates whether magnetization, electric polarization, momentum-dependent spin polarization, spin texture, anomalous Hall conductivity, and nonlinear-response tensors are allowed in each regime.

Crucially, the platform returns symmetry constraints rather than numerical predictions. It does not calculate how large a Hall current or an electric polarization will be. Instead, it determines whether a response is symmetry-possible, which directions or tensor components are allowed, and whether its origin can be traced to magnetic geometry or to spin-orbit coupling. That separation of powers is what makes the tool useful as a screening instrument: it can eliminate candidates whose symmetry forbids a desired response before anyone invests in first-principles calculations or crystal growth, and it can flag candidates whose symmetry guarantees one. Combined with an online service, open-source code, and a searchable database, the workflow scales from the analysis of a single material to high-throughput searches across entire structural families.

The team demonstrated the approach on three materials, each posing a different puzzle. The first concerns spin splitting: does it always require spin-orbit coupling? The two-dimensional altermagnet V2Se2O shows that it does not. In this material, the magnetic geometry alone already permits momentum-dependent spin splitting of the electronic bands, a property once considered inseparable from spin-orbit physics. FINDSPINGROUP then tracks what changes when spin-orbit coupling is added: the symmetry is lowered, the allowed components of spin polarization change, and an additional magnetic response becomes permitted. The result is a complete symmetry account of how a purely geometric effect and a relativistic effect layer on top of one another in the same compound.

The second puzzle asks whether magnetic order can create electric polarization. In MnSe2, the arrangement of magnetic moments breaks the inversion symmetry of the underlying non-magnetic crystal, allowing an electric polarization to emerge. The same magnetic order also permits momentum-dependent spin splitting. Because multiple symmetry-related magnetic states satisfy the same constraints, FINDSPINGROUP identifies candidate switching endpoints, revealing whether the electric polarization and the spin-dependent responses can be reversed separately or must reverse together. That question bears directly on device design, since independent control of distinct order parameters is far more valuable than a single locked switch. The third puzzle concerns the anomalous Hall effect in the non-coplanar antiferromagnet CoNb3S6. There, the magnetic geometry permits a Hall response even without spin-orbit coupling, while forbidding spin polarization throughout the Brillouin zone. When spin-orbit coupling is included, additional spin polarization and magnetization become symmetry-allowed. Together, the three cases demonstrate why observing a ferromagnetic-like response does not, by itself, reveal its origin: superficially similar effects can obey different symmetry rules and respond differently to external control.

Reproducibility posed its own challenge, and the team addressed it with a new data standard. The spin crystallographic information file, or SCIF, extends the familiar CIF and MCIF formats by storing the crystal structure together with its spin-group assignment, symmetry operations, coordinate transformations, and metadata. Like its predecessors, SCIF is designed to make symmetry information portable between researchers, software packages, and databases. The team is working with the IUCr Commission on Magnetic Structures to develop SCIF as a community standard for exchanging spin-group information, a step that could spare future researchers the ambiguity of unit-cell choices and spin-frame conventions that has long complicated comparisons between published analyses.

FINDSPINGROUP is available as a web service at findspingroup.com, with source code hosted on GitHub, lowering the barrier for groups that lack specialized symmetry expertise. For the broader field of unconventional magnetism, the platform arrives at a moment of rapid expansion, as altermagnets, non-coplanar antiferromagnets, and magnetism-driven ferroelectrics compete for attention as next-generation spintronic materials. By making the paired symmetry analysis fast, standardized, and shareable, the tool shifts the field’s focus from cataloging exotic responses to classifying their mechanisms, a shift that could accelerate the search for materials whose magnetic geometry and spin-orbit physics can be controlled independently, and ultimately for devices that exploit each contribution on its own terms.

Subject of Research: Symmetry-based separation of magnetic-geometry and spin-orbit-coupling contributions to unconventional magnetic properties using oriented spin space groups

Article Title: How can scientists disentangle the origins of unconventional magnetic properties?

Article References: How can scientists disentangle the origins of unconventional magnetic properties?. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: antiferromagnets, spin space group, oriented spin space group, magnetic space group, spin-orbit coupling, altermagnets, anomalous Hall effect, spin splitting, electric polarization, SCIF format, symmetry analysis, FINDSPINGROUP